Design, Integration and Implementation of an Intelligent and Self-recharging Drone System for Autonomous Power line Inspection

Today, many inspection domains utilize the benefits of drones to monitor and inspect infrastructure in an efficient manner. The energy grid is challenged by frequent and thorough inspection to stay operational. So far, drones have already been introduced to solve this challenge. However, the inspection drone still requires manual control and subsequent human examination of the captured photos and videos. This inspection process comes with a high inspection cost and is susceptible to human errors in fault finding. The proposed system builds on top of the authors' previous research to develop and verify an integrated drone system for autonomous power line inspection, enabling functioning mechanics through pneumatics, extension of operation time through energy harvesting, Artificial Intelligent (AI) fault detection, and system autonomy using navigational algorithms. An advanced drone system has been designed and manufactured for the mission, with the results demonstrating the capability to perform an autonomous inspection mission in conditions up to 30 kts wind speeds, being additionally able to detect faults in real-time at a high rate during drone motion. Furthermore, we demonstrate the ability to recharge the drone battery within 2.4 hours.